class_docstr: A context for controlling metrics recording when async checkpoint is used.
    
class_docstr_tok: ["A","context","for","controlling","metrics","recording","when","async","checkpoint","is","used","."]
code: def __init__(self):
      super().__init__()
      self._in_async_metrics_context = False
  
file_path: tensorflow/tensorflow/python/checkpoint/checkpoint_context.py
imports: import contextlib
  import threading
label_desc: Use image node_id 1 to create a new AsyncMetricsContext object from inherited base classes: threading with example: obj = AsyncMetricsContext()